Biologically Inspired Deep Learning Model for Efficient Foveal-Peripheral Vision

While abundant in biology, foveated vision is nearly absent from computational models and especially deep learning architectures. Despite considerable hardware improvements, training deep neural networks still presents a challenge and constraints complexity of models. Here we propose an end-to-end n...

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Bibliographic Details
Main Authors:	Hristofor Lukanov, Peter König, Gordon Pipa
Format:	article
Language:	EN
Published:	Frontiers Media S.A. 2021
Subjects:	space-variant vision active vision foveal vision peripheral vision deep learning-artificial neural network (DL-ANN) bottom-up attention Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Online Access:	https://doaj.org/article/dd5d9cfd27fd412e8e6bb0d0b7609983
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Biologically Inspired Deep Learning Model for Efficient Foveal-Peripheral Vision

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